Recurrence quantification analysis of heart rate variability during continuous incremental exercise test in obese subjects

The present paper concerns with a new description of changing in metabolism during incremental exercises test that permit an individually tailored program of exercises for obese subjects. We analyzed Heart Rate variability (HRV) from RR interval time series (tachogram) with an alternative approach, the recurrence quantification analysis (RQA), that allows a description of time series in term of its dynamic structure and is able to identify the phase transitions. A transition in cardiac signal dynamics was detected and it perfectly reflects the aerobic threshold (AerT), as identified by gas exchange during an incremental exercise test, revealing the coupling from respiratory system towards the heart. Moreover, our analysis shows that in the Recurrence Plot of RR interval it is possible to identify specific pattern that allow to identify phase transitions between different dynamic regimes. The perfectly match of the occurrence of the phase transitions with changes observed in the VO2 consumption, the gold standard approach to estimate thresholds, strongly support the possibility of using our analysis of RR interval to detect metabolic threshold. In conclusion we propose a novel nonlinear data analysis method that allows for an easy and personalized detection of thresholds both from professional and even from low-cost wearable devices, without the need of expensive gas analyzer.